Why Are Autism Rates Steadily Rising?
Stefania Sterling was just 21 when she had her son, Charlie. She was young and healthy, with no genetic issues apparent in either her or her husband's family, so she expected Charlie to be typical.
"It is surprising that the prevalence of a significant disorder like autism has risen so consistently over a relatively brief period."
It wasn't until she went to a Mommy and Me music class when he was one, and she saw all the other one-year-olds walking, that she realized how different her son was. He could barely crawl, didn't speak, and made no eye contact. By the time he was three, he was diagnosed as being on the lower functioning end of the autism spectrum.
She isn't sure why it happened – and researchers, too, are still trying to understand the basis of the complex condition. Studies suggest that genes can act together with influences from the environment to affect development in ways that lead to Autism Spectrum Disorder (ASD). But rates of ASD are rising dramatically, making the need to figure out why it's happening all the more urgent.
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Indeed, the CDC's latest autism report, released last week, which uses 2016 data, found that the prevalence of ASD in four-year-old children was one in 64 children, or 15.6 affected children per 1,000. That's more than the 14.1 rate they found in 2014, for the 11 states included in the study. New Jersey, as in years past, was the highest, with 25.3 per 1,000, compared to Missouri, which had just 8.8 per 1,000.
The rate for eight-year-olds had risen as well. Researchers found the ASD prevalence nationwide was 18.5 per 1,000, or one in 54, about 10 percent higher than the 16.8 rate found in 2014. New Jersey, again, was the highest, at one in 32 kids, compared to Colorado, which had the lowest rate, at one in 76 kids. For New Jersey, that's a 175 percent rise from the baseline number taken in 2000, when the state had just one in 101 kids.
"It is surprising that the prevalence of a significant disorder like autism has risen so consistently over a relatively brief period," said Walter Zahorodny, an associate professor of pediatrics at Rutgers New Jersey Medical School, who was involved in collecting the data.
The study echoed the findings of a surprising 2011 study in South Korea that found 1 in every 38 students had ASD. That was the the first comprehensive study of autism prevalence using a total population sample: A team of investigators from the U.S., South Korea, and Canada looked at 55,000 children ages 7 to 12 living in a community in South Korea and found that 2.64 percent of them had some level of autism.
Searching for Answers
Scientists can't put their finger on why rates are rising. Some say it's better diagnosis. That is, it's not that more people have autism. It's that we're better at detecting it. Others attribute it to changes in the diagnostic criteria. Specifically, the May 2013 update of the Diagnostic and Statistical Manual of Mental Disorders-5 -- the standard classification of mental disorders -- removed the communication deficit from the autism definition, which made more children fall under that category. Cynical observers believe physicians and therapists are handing out the diagnosis more freely to allow access to services available only to children with autism, but that are also effective for other children.
Alycia Halladay, chief science officer for the Autism Science Foundation in New York, said she wishes there were just one answer, but there's not. While she believes the rising ASD numbers are due in part to factors like better diagnosis and a change in the definition, she does not believe that accounts for the entire rise in prevalence. As for the high numbers in New Jersey, she said the state has always had a higher prevalence of autism compared to other states. It is also one of the few states that does a good job at recording cases of autism in its educational records, meaning that children in New Jersey are more likely to be counted compared to kids in other states.
"Not every state is as good as New Jersey," she said. "That accounts for some of the difference compared to elsewhere, but we don't know if it's all of the difference in prevalence, or most of it, or what."
"What we do know is that vaccinations do not cause autism."
There is simply no defined proven reason for these increases, said Scott Badesch, outgoing president and CEO of the Autism Society of America.
"There are suggestions that it is based on better diagnosis, but there are also suggestions that the incidence of autism is in fact increasing due to reasons that have yet been determined," he said, adding, "What we do know is that vaccinations do not cause autism."
Zahorodny, the pediatrics professor, believes something is going on beyond better detection or evolving definitions.
"Changes in awareness and shifts in how children are identified or diagnosed are relevant, but they only take you so far in accounting for an increase of this magnitude," he said. "We don't know what is driving the surge in autism recorded by the ADDM Network and others."
He suggested that the increase in prevalence could be due to non-genetic environmental triggers or risk factors we do not yet know about, citing possibilities including parental age, prematurity, low birth rate, multiplicity, breech presentation, or C-section delivery. It may not be one, but rather several factors combined, he said.
"Increases in ASD prevalence have affected the whole population, so the triggers or risks must be very widely dispersed across all strata," he added.
There are studies that find new risk factors for ASD almost on a daily basis, said Idan Menashe, assistant professor in the Department of Health at Ben-Gurion University of the Negev, the fastest growing research university in Israel.
"There are plenty of studies that find new genetic variants (and new genes)," he said. In addition, various prenatal and perinatal risk factors are associated with a risk of ASD. He cited a study his university conducted last year on the relationship between C-section births and ASD, which found that exposure to general anesthesia may explain the association.
Whatever the cause, health practitioners are seeing the consequences in real time.
"People say rates are higher because of the changes in the diagnostic criteria," said Dr. Roseann Capanna-Hodge, a psychologist in Ridgefield, CT. "And they say it's easier for children to get identified. I say that's not the truth and that I've been doing this for 30 years, and that even 10 years ago, I did not see the level of autism that I do see today."
Sure, we're better at detecting autism, she added, but the detection improvements have largely occurred at the low- to mid- level part of the spectrum. The higher rates of autism are occurring at the more severe end, in her experience.
A Polarizing Theory
Among the more controversial risk factors scientists are exploring is the role environmental toxins may play in the development of autism. Some scientists, doctors and mental health experts suspect that toxins like heavy metals, pesticides, chemicals, or pollution may interrupt the way genes are expressed or the way endocrine systems function, manifesting in symptoms of autism. But others firmly resist such claims, at least until more evidence comes forth. To date, studies have been mixed and many have been more associative than causative.
"Today, scientists are still trying to figure out whether there are other environmental changes that can explain this rise, but studies of this question didn't provide any conclusive answer," said Menashe, who also serves as the scientific director of the National Autism Research Center at BGU.
"It's not everything that makes Charlie. He's just like any other kid."
That inconclusiveness has not dissuaded some doctors from taking the perspective that toxins do play a role. "Autism rates are rising because there is a mismatch between our genes and our environment," said Julia Getzelman, a pediatrician in San Francisco. "The majority of our evolution didn't include the kinds of toxic hits we are experiencing. The planet has changed drastically in just the last 75 years –- it has become more and more polluted with tens of thousands of unregulated chemicals being used by industry that are having effects on our most vulnerable."
She cites BPA, an industrial chemical that has been used since the 1960s to make certain plastics and resins. A large body of research, she says, has shown its impact on human health and the endocrine system. BPA binds to our own hormone receptors, so it may negatively impact the thyroid and brain. A study in 2015 was the first to identify a link between BPA and some children with autism, but the relationship was associative, not causative. Meanwhile, the Food and Drug Administration maintains that BPA is safe at the current levels occurring in food, based on its ongoing review of the available scientific evidence.
Michael Mooney, President of St. Louis-based Delta Genesis, a non-profit organization that treats children struggling with neurodevelopmental delays like autism, suspects a strong role for epigenetics, which refers to changes in how genes are expressed as a result of environmental influences, lifestyle behaviors, age, or disease states.
He believes some children are genetically predisposed to the disorder, and some unknown influence or combination of influences pushes them over the edge, triggering epigenetic changes that result in symptoms of autism.
For Stefania Sterling, it doesn't really matter how or why she had an autistic child. That's only one part of Charlie.
"It's not everything that makes Charlie," she said. "He's just like any other kid. He comes with happy moments. He comes with sad moments. Just like my other three kids."
Artificial Intelligence Needs Doctors As Much As They Need It
The media loves to hype concerns about artificial intelligence: What if machines become super-intelligent and self-aware? How will humanity compete and survive? But artificial intelligence today is a far cry from a robot takeover. "AI" is a catch-all term that often refers to machine training or machine learning: There is an abundance of data, vastly more than the human mind can assimilate, being tagged, captured and stored. This systematic data processing requires methodologies that can put it in usable form and formats. While these new developments stoke fear in some corners, the ability to predict outcomes is generally seen as a good thing, as it can mitigate risks and even save lives.
We, collectively, want AI even though it is seldom expressed this way.
The prospects and attempts toward artificial intelligence has been with us for decades. Only recently have the underlying technologies and infrastructure--including computer processing, storage, networking speed and advanced software platforms--become omnipresent. These technological advances enabled the implementation of data mining concepts and the subsequent advantages that were not feasible just a decade ago.
AI is fantastical by vision, evolutionary by experience, and disruptive upon reflection. In the world of health care, AI is already transforming research and clinical practice. We, collectively, want AI even though it is seldom expressed this way. What we, the patient population, patient advocates and caregivers, agree on and want is: (1) timely, precise and inexpensive diagnoses of our ailments, injuries and disorders; (2) timely, personalized, highly effective and efficient courses of therapies; and (3) expedited recovery with minimum deficits, complications and recurrence.
"Artificial intelligence and machine learning will impact healthcare as profoundly as the discovery of the microscope."
Implicitly, we all are saying that we want our healthcare systems and clinicians to accomplish truly inhuman feats: to incorporate all sources of structured data (such as published statistics and reports) and unstructured data (including news articles, conversational analysis by care givers, nuances of similar cases, talks at professional societies); to analyze the data sourced and uncover patterns, reveal side effects, define probable success and outcomes; and to present the best personalized course of treatment for the patient that addresses the ailment and mitigates associated risks. It is hard to argue against any of this.
In a recent published interview, Keith J. Dreyer, executive director of the Massachusetts General Hospital and Brigham and Women's Hospital Center for Clinical Data Science, says that "artificial intelligence and machine learning will impact healthcare as profoundly as the discovery of the microscope."
But as AI helps physicians in profound ways, like detecting subtle lesions on scans or distinguishing the symptoms of a stroke from a brain tumor, we humans can't get too complacent. Evolving AI platforms will provide more sophisticated sets of "tools" to address both mundane and complex medical challenges, albeit with humans very much in the mix and routinely at the helm.
Humans do not appear endangered to be replaced anytime soon.
Human beings are capable of a level of nuance and contextual understanding of complex medical scenarios and, consequently, do not appear endangered to be replaced anytime soon. These platforms will do some heavy lifting for sure and provide considerable assistance across the healthcare industry. But human involvement is crucial, as we are best at adaptive learning, cognition, ensuring accuracy of the data, and continually providing feedback to improve the machine learning components of the AI platforms that the health industry will increasingly rely upon.
The human/machine interface is not binary; there is no line in the sand. It is fuzzy and evolutionary, a synchronicity that we all will surely witness and experience. In the future, it may be possible that all recorded knowledge, including genetic, genomic and laboratory data, from structured and unstructured sources, can be at the fingertips of your clinician, and then factored into diagnosing your condition and prescribing your course of treatment. This is precision and personalized medicine on a grand scale applied at the micro level--you!
But none of this will diminish the importance of doctors, nurses and all assortment of care providers. Though they all will undoubtedly become more effective with such awesome AI assistance, their job will always be to heal you with compassion, wisdom, and kindness, for the essence of humanity cannot be automated.
This Revolutionary Medical Breakthrough Is Not a Treatment or a Cure
What is a disease? This seemingly abstract and theoretical question is actually among the most practical questions in all of biomedicine. How patients are diagnosed, treated, managed and excused from various social and moral obligations hinges on the answer that is given. So do issues of how research is done and health care paid for. The question is also becoming one of the most problematic issues that those in health care will face in the next decade.
"The revolution in our understanding of the human genome, molecular biology, and genetics is creating a huge--if little acknowledged--shift in the understanding of what a disease is."
That is because the current conception of disease is undergoing a revolutionary change, fueled by progress in genetics and molecular biology. The consequences of this shift in the definition of disease promise to be as impactful as any other advance in biomedicine has ever been, which is admittedly saying a lot for what is in essence a conceptual change rather than one based on an empirical scientific advance.
For a long time, disease was defined by patient reports of feeling sick. It was not until the twentieth century that a shift occurred away from subjective reports of clusters of symptoms to defining diseases in terms of physiological states. Doctors began to realize that not all symptoms of fever represented the presence of the same disease. Flu got distinguished from malaria. Diseases such as hypertension, osteoporosis, cancer, lipidemia, silent myocardial infarction, retinopathy, blood clots and many others were recognized as not producing any or slight symptoms until suddenly the patient had a stroke or died.
The ability to assess both biology and biochemistry and to predict the consequences of subclinical pathological processes caused a distinction to be made between illness—what a person experiences—and disease—an underlying pathological process with a predictable course. Some conditions, such as Gulf War Syndrome, PTSD, many mental illnesses and fibromyalgia, remain controversial because no underlying pathological process has been found that correlates with them—a landmark criterion for diagnosing disease throughout most of the last century.
"Diseases for which no relationship had ever been posited are being lumped together due to common biochemical causal pathways...that are amenable to the same curative intervention."
The revolution in our understanding of the human genome, molecular biology, and genetics is creating a huge--if little acknowledged--shift in the understanding of what a disease is. A better understanding of the genetic and molecular roots of pathophysiology is leading to the reclassification of many familiar diseases. The test of disease is now not the pathophysiology but the presence of a gene, set of genes or molecular pathway that causes pathophysiology. Just as fever was differentiated into a multitude of diseases in the last century, cancer, cognitive impairment, addiction and many other diseases are being broken or split into many subkinds. And other diseases for which no relationship had ever been posited are being lumped together due to common biochemical causal pathways or the presence of similar dangerous biochemical products that are amenable to the same curative intervention, no matter how disparate the patients' symptoms or organic pathologies might appear.
We used to differentiate ovarian and breast cancers. Now we are thinking of them as outcomes of the same mutations in certain genes in the BRCA regions. They may eventually lump together as BRCA disease.
Other diseases such as familial amyloid polyneuropathy (FAP) which causes polyneuropathy and autonomic dysfunction are being split apart into new types or kinds. The disease is the product of mutations in the transthyretin gene. It was thought to be an autosomal dominant disease with symptomatic onset between 20-40 years of age. However, as genetic testing has improved, it has become clear that FAP's traditional clinical presentation represents a relatively small portion of those with FAP. Many patients with mutations in transthyretin — even mutations commonly seen in traditional FAP patients — do not fit the common clinical presentation. As the mutations begin to be understood, some people that were previously thought to have other polyneuropathies, such as chronic inflammatory demyelinating neuropathy, are now being rediagnosed with newly discovered variants of FAP.
"We are at the start of a major conceptual shift in how we organize the world of disease, and for that matter, health promotion."
Genome-wide association studies are beginning to find many links between diseases not thought to have any connection or association. For example some forms of diabetes, rheumatoid arthritis and thyroid disease may be the products of a small family of genetic mutations.
So why is this shift toward a genetic and molecular diagnostics likely to shake up medicine? One obvious way is that research projects may propose to recruit subjects not according to current standards of disease but on the basis of common genetic mutations or similar errors in biochemical pathways. It won't matter in a future study if subjects in a trial have what today might be termed nicotine addiction or Parkinsonism. If the molecular pathways producing the pathology are the same, then both groups might well wind up in the same trial of a drug.
In addition, what today look like common maladies—pancreatic cancer, severe depression, or acne, for example, could wind up being subdivided into so many highly differentiated versions of these conditions that each must be treated as what we now classify as a rare or ultra-rare disease. Unique biochemical markers or genetic messages may see many diseases broken into a huge number of distinct individual disease entities.
Patients may find that common genetic pathways or multiple effects from a single gene may create new alliances for fund-raising and advocacy. Groups fighting to cure mental and physical illnesses may wind up forgetting about their outward differences in the effort to alter genes or attack common protein markers.
Disease classification appears stable to us—until it isn't. And we are at the start of a major conceptual shift in how we organize the world of disease, and for that matter, health promotion. Classic reductionism, the view that all observable biological phenomena can be explained in terms of underlying chemical and physical principles, may turn out not to be true. But the molecular and genetic revolutions churning through medicine are illustrating that reductionism is going to have an enormous influence on disease classification. That is not a bad thing, but it is something that is going to take a lot to get used to.